جذبت الكشف عن المشاعر من وظائف وسائل التواصل الاجتماعي اهتماما ملحوظا من مجتمع معالجة اللغة الطبيعية (NLP) في السنوات الأخيرة.تختلف طرق الحصول على ملصقات ذهبية لتدريب واختبار أنظمة الكشف عن المشاعر التلقائية بشكل كبير من دراسة واحدة إلى أخرى، وتشكل مسألة موثوقية الملصقات الذهبية وتحصل على نتائج التصنيف.تستكشف هذه الدراسة بشكل منهجي عدة طرق للحصول على ملصقات ذهبية لنموذج EKMAN الخاص ببيانات Twitter وتأثير الاستراتيجية المختارة في نتائج التصنيف اليدوي.
Emotion detection from social media posts has attracted noticeable attention from natural language processing (NLP) community in recent years. The ways for obtaining gold labels for training and testing of the systems for automatic emotion detection differ significantly from one study to another, and pose the question of reliability of gold labels and obtained classification results. This study systematically explores several ways for obtaining gold labels for Ekman's emotion model on Twitter data and the influence of the chosen strategy on the manual classification results.
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